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Over the last few decades, multiple-instance learning (MIL) has been successfully utilized to solve the content-based image/video retrieval (CBIR/CBVR) problem, in which a bag corresponds to a video scene and an instance corresponds to a frame caption. However, existing feature representation schemes are not effective enough to use MIL to detect video caption frames from news video, which hinders...
Over the last few decades, Content-based image/video retrieval (CBIR/CBVR) problem have developed a new height. As one of the most impartment methods of CBVR, video caption extraction obtained more and more application. A large number of techniques have been proposed to address this problem, we summarized most of the video caption extraction methods, analyzed the advantage and disadvantage of the...
To improve the performance of multi-pose face detection, the AdaboostSVM algorithm based on multi-feature fusion is proposed in this paper. Firstly, the Haar-like features and the triangular integral features are introduced and the edge-orientation field features based on morphological gradient are presented. Then, the AdaboostSVM Algorithm based on the above three kinds of features is proposed. The...
In order to improve the training convergence speed and detection accuracy of diverse AdaBoostSVM, an improved algorithm is proposed according to the asymmetry in face detection. In the algorithm, the weight of each weak learner, which represents importance of each weak learner, is determined by the error rate and the recognition capability of the weak learner for the face samples. The results of the...
Micorarray data are often extremely asymmetric in dimensionality, such as thousands or even tens of thousands of genes and a few hundreds of samples. Such extreme asymmetry between the dimensionality of genes and samples can lead inaccurate diagnosis of disease in clinic. Therefore, it has been shown that selecting a small set of marker genes can lead to improved classification accuracy. In this paper,...
The image semantic classification is new focus in the image classification field, the traditional classification algorithm is based on the low level visual features, but there is an enormous semantic gap problem between the low-level visual features and high-level semantic information of images. An image semantic classification approach is proposed based on Kernel PCA Support Vector Machines (KPCA...
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